Fill-Mask
Transformers
PyTorch
Vietnamese
xlm-roberta
Vietnamese
Social Media
Vietnamese Pre-trained Model
Sentiment Analysis
Hate Speech Detection
Spam Detection
Emotionn Recognition
Instructions to use uitnlp/visobert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uitnlp/visobert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="uitnlp/visobert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("uitnlp/visobert") model = AutoModelForMaskedLM.from_pretrained("uitnlp/visobert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Update paper link
Browse files
README.md
CHANGED
|
@@ -11,7 +11,7 @@ ViSoBERT is the state-of-the-art language model for Vietnamese social media task
|
|
| 11 |
- ViSoBERT is the first monolingual MLM ([XLM-R](https://github.com/facebookresearch/XLM#xlm-r-new-model) architecture) built specifically for Vietnamese social media texts.
|
| 12 |
- ViSoBERT outperforms previous monolingual, multilingual, and multilingual social media approaches, obtaining new state-of-the-art performances on four downstream Vietnamese social media tasks.
|
| 13 |
|
| 14 |
-
The general architecture and experimental results of ViSoBERT can be found in our [paper](https://
|
| 15 |
|
| 16 |
@inproceedings{nguyen-etal-2023-visobert,
|
| 17 |
title = "{V}i{S}o{BERT}: A Pre-Trained Language Model for {V}ietnamese Social Media Text Processing",
|
|
|
|
| 11 |
- ViSoBERT is the first monolingual MLM ([XLM-R](https://github.com/facebookresearch/XLM#xlm-r-new-model) architecture) built specifically for Vietnamese social media texts.
|
| 12 |
- ViSoBERT outperforms previous monolingual, multilingual, and multilingual social media approaches, obtaining new state-of-the-art performances on four downstream Vietnamese social media tasks.
|
| 13 |
|
| 14 |
+
The general architecture and experimental results of ViSoBERT can be found in our [paper](https://aclanthology.org/2023.emnlp-main.315/):
|
| 15 |
|
| 16 |
@inproceedings{nguyen-etal-2023-visobert,
|
| 17 |
title = "{V}i{S}o{BERT}: A Pre-Trained Language Model for {V}ietnamese Social Media Text Processing",
|